← Back to cohort
Correction to: Solve-RD: systematic pan-European data sharing and collaborative analysis to solve rare diseases
Birte Zurek, Kornelia Ellwanger, Lisenka E.L.M. Vissers, Rebecca Schüle, Matthis Synofzik, Ana Töpf, Richarda M. de Voer, Steven Laurie, Leslie Matalonga, Christian Gilissen, Stephan Ossowski, Peter A.C. ’t Hoen, Antonio Vitobello, Julia M. Schulze‐Hentrich, Olaf Rieß, Han G. Brunner, Anthony J. Brookes, Ana Rath, Gisèle Bonne, Gulcin Gumus, Alain Verloès, Nicoline Hoogerbrugge, Teresinha Evangelista, Tina Harmuth, Morris A. Swertz, Dylan Spalding, Alexander Hoischen, Sergi Beltrán, Holm Graeßner, Tobias B. Haack, German Demidov, Marc Sturm, Christoph Keßler, Melanie Wayand, Carlo Wilke, Andreas Traschütz, Lüdger Schöls, Holger Hengel, Peter Heutink, Hans Scheffer, Wouter Steyaert, Karolis Sablauskas, Erik-Jan Kamsteeg, Bart van de Warrenburg, Nienke van Os, Iris te Paske, Erik Janssen, Elke de Boer, Marloes Steehouwer, Burcu Yaldız, Tjitske Kleefstra, Colin Veal, Spencer Gibson, Marc Wadsley, Mehdi Mehtarizadeh, Umar Riaz, Greg Warren, Farid Yavari Dizjikan, Thomas Shorter, Volker Straub, C. Marini Bettolo, Sabine Specht, Jill Clayton‐Smith, Siddharth Banka, Elizabeth Alexander, Adam Jackson, Laurence Faivre, Christel Thauvin, Anne‐Sophie Denommé‐Pichon, Yannis Duffourd, Émilie Tisserant, Ange‐Line Bruel, Christine Peyron, Aurore Pélissier, Marta Gut, Davide Piscia, Anastasios Papakonstantinou, Gemma Bullich, Alberto Corvò, Carles García, Marcos Fernández-Callejo, Carles Hernandéz-Ferrer, Daniel Picó, Ida Paramonov, Hanns Lochmüller, Virginie Bros‐Facer, Marc Hanauer, Annie Olry, David Lagorce, Svitlana Havrylenko, Katia Izem, Fanny Rigour, Giovanni Stévanin, Alexandra Dürr, Claire-Sophie Davoine, Léna Guillot‐Noël, Anna Heinzmann, Giulia Coarelli, Valérie Allamand, Isabelle Nelson, Rabah Ben Yaou, Corinne Métay, B. Eymard, Enzo Cohen, António Atalaia, Tanya Stojkovic, Milan Macek, Marek Turnovec, Dana Thomasová, Radka Pourová Kremliková, Věra Franková, Markéta Havlovicová, Vlastimil Kremlik, Helen Parkinson, Thomas Keane, Alexander Senf, Peter N. Robinson, Daniel Daniš, Glenn Robert, Alessia Costa, Christine Patch, Henry Houlden, Mary M. Reilly, Jana Vandrovcová, Francesco Muntoni, Irina Zaharieva, Anna Sárközy, Vincent Timmerman, Jonathan Baets, Liedewei Van de Vondel, Danique Beijer, Peter De Jonghe, Vincenzo Nigro, Sandro Banfi, Annalaura Torella, Francesco Musacchia, Giulio Piluso, Alessandra Ferlini, Rita Selvatici, Rachele Rossi, Marcella Neri, Stefan Aretz, Isabel Spier, Anna Katharina Sommer, Sophia Peters, Carla Oliveíra, José Garcia‐Pelaez, Ana Rita Matos, Celina São José, Marta Ferreira, Irene Gullo, Susana Fernandes, Luzia Garrido, Pedro Ferreira, Fátima Carneiro, Lennart Johansson, Joeri K. van der Velde, Gerben van der Vries, Pieter B. Neerincx, Dieuwke Roelofs-Prins, Sebastian Köhler, Alison Metcalfe, Séverine Drunat, Caroline Rooryck, Aurélien Trimouille, Raffaele Castello, Manuela Morleo, Michele Pinelli, Alessandra Varavallo, Manuel Posada de la Paz, Eva Bermejo, Estrella López Martín, Beatriz Martínez–Delgado, F. Javier Alonso García de la Rosa, Andrea Ciolfi, Bruno Dallapiccola, Simone Pizzi, Francesca Clementina Radio, Marco Tartaglia, Alessandra Renieri, Elisa Benetti, Péter Balicza, Mária Judit Molnár, Aleš Maver, Borut Peterlin, Alexander Münchau, Katja Lohmann, Rebecca Herzog, Martje G. Pauly, Alfons Macaya, Anna Marcé‐Grau, Andres Nascimiento Osorio, Daniel Natera‐de Benito, Rachel Thompson, Kiran Polavarapu, David Beeson, Judith Cossins, Pedro M. Rodríguez Cruz, Peter Hackman, Mridul Johari, Marco Savarese, Bjarne Udd, Rita Horváth, Gabriel Capellá, Laura Valle, Elke Holinski‐Feder, Andreas Laner, Verena Steinke‐Lange, Evelin Schröck, Andreas Rump
Bibliographic record
VenueEuropean Journal of Human Genetics · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsChildren's Hospital of Eastern OntarioUniversity of Ottawa
Fundersnot available
KeywordsComputational biologyComputer scienceData sharingData scienceInformation retrievalMedicineBiologyAlternative medicinePathology
Abstract
No abstract in any covered source. Its absence is recorded, not treated as a negative.
No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.183
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reproducibility · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.990
Threshold uncertainty score0.425
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.183 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.127 | 0.054 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
Opus teacher head0.023
GPT teacher head0.279
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
Study designNot applicable
DomainReproducibility
GenreOther
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".
Quick stats
Citations1
Published2021
Admission routes1
Has abstractno